| Characteristic | Overall1 |
Acute Hypoxaemic Respiratory Failure Category
|
|||
|---|---|---|---|---|---|
| None (PF >300)1 | Mild (PF 200-300)1 | Moderate (PF 100-200)1 | Severe (PF < 100)1 | ||
| Number of Patients | 662,612 | 324,761 | 181,499 | 128,227 | 28,125 |
| Median Age in Years (IQR) | 66 (53-75) | 65 (50-75) | 68 (56-76) | 67 (55-75) | 65 (52-75) |
| Age Category, Years | |||||
| <44 | 99,985 (15%) | 60,314 (19%) | 19,751 (11%) | 15,515 (12%) | 4,405 (16%) |
| >84 | 47,408 (7.2%) | 24,404 (7.5%) | 13,341 (7.4%) | 7,985 (6.2%) | 1,678 (6.0%) |
| 45-64 | 198,888 (30%) | 94,398 (29%) | 54,892 (30%) | 40,546 (32%) | 9,052 (32%) |
| 65-84 | 315,855 (48%) | 145,422 (45%) | 93,376 (51%) | 64,083 (50%) | 12,974 (46%) |
| Gender | |||||
| Female | 275,502 (42%) | 146,046 (45%) | 70,722 (39%) | 48,420 (38%) | 10,314 (37%) |
| Male | 386,572 (58%) | 178,437 (55%) | 110,613 (61%) | 79,734 (62%) | 17,788 (63%) |
| Intersex/Indeterminate | 378 (<0.1%) | 200 (<0.1%) | 108 (<0.1%) | 52 (<0.1%) | 18 (<0.1%) |
| Unknown | 160 (<0.1%) | 78 (<0.1%) | 56 (<0.1%) | 21 (<0.1%) | 5 (<0.1%) |
| Median APACHE II Score (IQR) | 15 (11-20) | 13 (10-18) | 15 (12-20) | 18 (14-24) | 23 (18-30) |
| Median APACHE III Score (IQR) | 50 (38-66) | 45 (34-59) | 51 (39-66) | 59 (46-77) | 75 (57-99) |
| Median ANZROD (IQR) | 0.02 (0.01-0.07) | 0.01 (0.00-0.04) | 0.02 (0.01-0.07) | 0.04 (0.01-0.17) | 0.14 (0.03-0.45) |
| Median SOFA (IQR) | 4 (2-6) | 3 (1-4) | 4 (3-6) | 5 (4-7) | 7 (5-10) |
| Admission Diagnosis | |||||
| Medical | 197,553 (30%) | 74,842 (24%) | 51,037 (29%) | 55,029 (44%) | 16,645 (61%) |
| Post-Operative | 191,807 (30%) | 112,503 (35%) | 53,720 (30%) | 22,809 (18%) | 2,775 (10%) |
| Sepsis | 52,894 (8.2%) | 23,625 (7.5%) | 14,518 (8.2%) | 11,587 (9.2%) | 3,164 (12%) |
| Trauma/Neurosurgery | 77,311 (12%) | 50,410 (16%) | 18,202 (10%) | 7,660 (6.1%) | 1,039 (3.8%) |
| Cardiac Surgery | 128,286 (20%) | 55,633 (18%) | 40,283 (23%) | 28,504 (23%) | 3,866 (14%) |
| COVID Penumonitis (Proven) | 4,865 (0.7%) | 265 (<0.1%) | 657 (0.4%) | 2,569 (2.0%) | 1,374 (4.9%) |
| Admission Source | |||||
| Emergency Department | 158,625 (24%) | 67,604 (21%) | 41,263 (23%) | 38,897 (31%) | 10,861 (40%) |
| Operating Theatre/Recovery | 387,416 (59%) | 214,294 (67%) | 109,261 (61%) | 56,536 (45%) | 7,325 (27%) |
| Ward | 74,547 (11%) | 25,911 (8.1%) | 19,449 (11%) | 22,067 (18%) | 7,120 (26%) |
| ICU, Same Hospital | 658 (0.1%) | 276 (<0.1%) | 168 (<0.1%) | 165 (0.1%) | 49 (0.2%) |
| Other Hospital | 29,930 (4.6%) | 12,646 (3.9%) | 8,065 (4.5%) | 7,396 (5.9%) | 1,823 (6.7%) |
| Direct from Home | 675 (0.1%) | 298 (<0.1%) | 172 (<0.1%) | 158 (0.1%) | 47 (0.2%) |
| Hospital Type | |||||
| Tertiary | 300,036 (45%) | 141,908 (44%) | 82,532 (45%) | 62,179 (48%) | 13,417 (48%) |
| Metropolitan | 94,431 (14%) | 39,233 (12%) | 25,487 (14%) | 22,858 (18%) | 6,853 (24%) |
| Rural / Regional | 62,039 (9.4%) | 25,484 (7.8%) | 17,587 (9.7%) | 15,416 (12%) | 3,552 (13%) |
| Private | 206,106 (31%) | 118,136 (36%) | 55,893 (31%) | 27,774 (22%) | 4,303 (15%) |
| Chronic Respiratory Disease | 47,897 (7.2%) | 14,304 (4.4%) | 15,910 (8.8%) | 14,645 (11%) | 3,038 (11%) |
| Chronic CVS Disease | 60,583 (9.1%) | 26,453 (8.1%) | 17,915 (9.9%) | 13,388 (10%) | 2,827 (10%) |
| Chronic Hepatic Disease | 12,012 (1.8%) | 5,202 (1.6%) | 3,383 (1.9%) | 2,749 (2.1%) | 678 (2.4%) |
| Chronic Renal Disease | 23,002 (3.5%) | 10,724 (3.3%) | 6,478 (3.6%) | 4,720 (3.7%) | 1,080 (3.8%) |
| Frailty | |||||
| Fit/Well | 279,572 (59%) | 147,891 (63%) | 73,133 (57%) | 48,604 (53%) | 9,944 (51%) |
| Mild | 142,545 (30%) | 64,841 (28%) | 41,025 (32%) | 30,223 (33%) | 6,456 (33%) |
| Moderate/Severe | 50,901 (11%) | 20,270 (8.7%) | 15,069 (12%) | 12,546 (14%) | 3,016 (16%) |
| 1 n; Median (Q1-Q3); n (%) | |||||
Validation Study of the Use of PF Ratio for Patients with Acute Hypoxaemic Respiratory Failure Admitted to Australian and New Zealand Intensive Care Units
Statistical Analysis
1 Introduction
This is an explanation of the statistical analysis for the study validating the use of PaO2:FiO2 ratio in patients admitted to ICU with acute hypoxaemic respiratory failure.
2 Methods
This is a retrospective study using data from the Australian and New Zealand Intensive Care Society (ANZICS) adult ICU patient database (APD). This manuscript has been prepared and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement.
2.1 Patient Population
We included all patients in the ANZICS APD from 01/01/2018 to 31/12/2022.
2.2 Aims and Objectives
- Determine the association between PaO2:FiO2 ratio and hospital mortality.
- Determine the association between PaO2:FiO2 ratio and ICU mortality.
- Determine the association between PaO2:FiO2 ratio and mortality at other timepoints (28 day, 6 months, 12 months).
- Validate the PaO2:FiO2 ratio as a diagnostic tool for prediction of hospital mortality, and mortality at other times (ICU, 28-day, 6 months, 12 months).
- Determine the validity of the PaO2:FiO2 ratio in predicting hospital mortality in pre-specified subgroups (invasive ventilation, ventilatory support, age, sex, admission diagnoses, frailty categories, presence of treatment limitations).
2.3 Statistical Analysis
We summarized baseline ICU and patient-level characteristics and unadjusted outcomes using standard descriptive statistics. For categorical data, we used counts and percentages, and for continuous data we used mean ± standard deviation (SD) or median (interquartile range, IQR) as appropriate depending on the distribution of data.
2.3.1 Association Between PaO2:FiO2 Ratio and Hospital Mortality
The unadjusted association between PaO2:FiO2 ratio and hospital mortality was evaluated visually as a continuous, non-linear variable using restricted cubic splines with 4 knots. Specific unadjusted hospital mortality values for standard PaO2:FiO2 ratio values were also calculated through interrogation of the spline curve.
2.3.2 Validation of PaO2:FiO2 ratio in Predicting Hospital Mortality
To determine the validitiy of the PaO2:FiO2 ratio, the area under the receiver operator characteristic curve (AUCROC) was calculated. 95% confidence intervals around the AUC were calculated using 1,000 bootstrap samples.
To determine the optimal cut-off of PaO2:FiO2 ratio in predicting hospital mortality, receiver operator characteristic curves (ROC) were generated. A cut-off level representing the highest sum of sensitivity and specificity hased on each patients PaO2:FiO2 ratio was calculated using the Youden method1. In this method, the sensitivity and specificity was calculated over a range of PaO2:FiO2 ratios. For each value, the Youden’s J index was calculated by using the following formula (Youden = Sensitivity + Specificity - 1). The value that corresponds to the highest Youden index was identified as the optimal cut-off, reflecting the highest sum of sensitivity and specifity. We also calculated the sensitivity, specificity, negative predictive value and positive predictive value for this cut-off.
2.3.3 Subgroup Analysis
Patients were analysed for validation of the PaO2:FiO2 ratio in prediction of hospital mortality in the following subgroups: receiving invasive ventilation during the index ICU admission, receiving of other respiratory support (eg non-invasive ventilation, extracorporeal membrane oxygenation) during the ICU admission, sex, age categories, admission diagnoses (medical, cardiac surgery, neurosurgery/trauma, sepsis, post-operative), frailty category (fit/well, mild, moderate, severe frailty) and the presence of treatment limitation status on ICU admission. The same methodology as above was employed. Comparison of each subgroup (ie IPPV vs Non-IPPV) was performed using DeLong’s method2.
As there were >800,000 patients in the dataset, a 2-sided p-value of 0.001 was used for statistical significance. Given that there is an increased risk of Type-1 error with multiple testing, the results of the secondary objectives should be viewed as exploratory. Hence, no adjustment for multiplicity was used. Only patients with complete data for all covariates were included in the analysis. Statistical analyses were performed using R Version 4.3.1 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria) and RStudio Version 2023.12.1 (Posit Software, PBC, Boston, MA). Packages used for analysis included tidytable3, tidyverse4, data.table5, gtsummary6, gt7, cutpointr8 and pROC9.
3 Results
Of 662,612 patients admitted to 211 ICUs during the study period, 337,851 (51.0%) patients had acute hypoaxemic respiratory failure. Of this cohort, 181,499 (27.4%) had mild AHRF, 128,227 (19.4%) had moderate AHRF and 28,125 (4.2%) had severe AHRF.
3.1 Patient Demographics
Below are the demographic tables. This table has the 4 AHRF categories (none, mild, moderate, severe) to look at the breakdown of patients within each AHRF category.
3.2 ICU Supports
| Characteristic | Overall1 |
Acute Respiratory Failure Category
|
|||
|---|---|---|---|---|---|
| None (PF >300)1 | Mild (PF 200-300)1 | Moderate (PF 100-200)1 | Severe (PF < 100)1 | ||
| IPPV on Day 1 | 245,116 (37%) | 94,906 (29%) | 69,017 (38%) | 63,782 (50%) | 17,411 (62%) |
| IPPV | 254,129 (38%) | 97,466 (30%) | 71,640 (39%) | 66,789 (52%) | 18,234 (65%) |
| Hours of IPPV (Pts that received IPPV) | 18 (8, 62) | 15 (7, 41) | 16 (7, 49) | 24 (10, 89) | 51 (16, 156) |
| NIV | 69,929 (11%) | 13,271 (4.1%) | 20,584 (11%) | 28,181 (22%) | 7,893 (28%) |
| Hours of NIV (Pts that received NIV) | 13 (5, 33) | 9 (4, 23) | 13 (5, 30) | 15 (6, 38) | 15 (5, 40) |
| ECMO | 2,120 (0.3%) | 295 (<0.1%) | 268 (0.1%) | 683 (0.5%) | 874 (3.1%) |
| Inotropes/Vasopressors | 266,049 (40%) | 109,241 (34%) | 74,969 (41%) | 64,608 (50%) | 17,231 (61%) |
| Tracheostomy | 8,856 (1.3%) | 2,894 (0.9%) | 2,194 (1.2%) | 2,684 (2.1%) | 1,084 (3.9%) |
| Acute Kidney Injury | 30,315 (4.6%) | 10,503 (3.2%) | 7,892 (4.3%) | 8,427 (6.6%) | 3,493 (12%) |
| Renal Replacement Therapy | 27,885 (4.2%) | 8,775 (2.7%) | 6,738 (3.7%) | 8,515 (6.6%) | 3,857 (14%) |
| 1 n (%); Median (Q1, Q3) | |||||
3.3 ICU & Hospital Outcomes
| Characteristic | Overall1 |
Acute Respiratory Failure Category
|
|||
|---|---|---|---|---|---|
| None (PF >300)1 | Mild (PF 200-300)1 | Moderate (PF 100-200)1 | Severe (PF < 100)1 | ||
| Hospital Mortality | 57,052 (8.6%) | 15,797 (4.9%) | 14,291 (7.9%) | 18,247 (14%) | 8,717 (31%) |
| ICU Mortality | 38,681 (5.9%) | 9,138 (2.8%) | 8,897 (4.9%) | 13,212 (10%) | 7,434 (26%) |
| Mean ICU Length of Stay in Days (SD) | 3.33 (5.57) | 2.60 (4.19) | 3.23 (5.32) | 4.64 (7.13) | 6.35 (9.50) |
| Median ICU Length of Stay in Days (IQR) | 1.89 (0.96-3.70) | 1.63 (0.90-2.88) | 1.92 (0.98-3.67) | 2.79 (1.46-5.15) | 3.48 (1.54-7.43) |
| Mean Hospital Length of Stay in Days (SD) | 15 (86) | 14 (87) | 15 (84) | 16 (88) | 17 (76) |
| Median Hospital Length of Stay in Days (IQR) | 9 (5-15) | 8 (4-14) | 9 (5-16) | 10 (6-17) | 10 (4-19) |
| 1 n (%); Mean (SD); Median (Q1-Q3) | |||||
3.4 Mortality Outcomes
Below are the cumulative incidences of hospital mortality, ICU mortality, 6-month mortality and 12-month mortality.
| Characteristic | Overall1 |
Acute Hypoxaemic Respiratory Failure Category
|
|||
|---|---|---|---|---|---|
| None (PF >300)1 | Mild (PF 200-300)1 | Moderate (PF 100-200)1 | Severe (PF < 100)1 | ||
| Number of Patients | 662,612 | 324,761 | 181,499 | 128,227 | 28,125 |
| ICU Mortality | 38,681 (5.9%) | 9,138 (2.8%) | 8,897 (4.9%) | 13,212 (10%) | 7,434 (26%) |
| Hospital Mortality | 57,052 (8.6%) | 15,797 (4.9%) | 14,291 (7.9%) | 18,247 (14%) | 8,717 (31%) |
| 28-Day Mortality | 53,397 (8.1%) | 15,715 (4.8%) | 13,874 (7.6%) | 16,882 (13%) | 6,926 (25%) |
| 90-Day Mortality | 70,842 (11%) | 23,570 (7.3%) | 18,689 (10%) | 20,734 (16%) | 7,849 (28%) |
| 180-Day Mortality | 84,821 (13%) | 30,530 (9.4%) | 22,542 (12%) | 23,380 (18%) | 8,369 (30%) |
| 1-Year Mortality | 104,441 (16%) | 40,498 (12%) | 27,923 (15%) | 27,008 (21%) | 9,012 (32%) |
| 1 n; n (%) | |||||
3.5 Primary Outcome: Hospital Mortality
3.6 Primary & Secondary Outcomes: Discriminator Characteristics
| Criteria | Hospital Mortality | ICU Mortality | 28-Day Mortality | 90-Day Mortality | 180-Day Mortality | 1-Year Mortality |
|---|---|---|---|---|---|---|
| Optimal Cutpoint | 230.000 | 224.286 | 233.333 | 233.333 | 233.333 | 233.333 |
| Sensitivity (Sn) | 0.561 | 0.602 | 0.546 | 0.502 | 0.471 | 0.441 |
| Specificity (Sp) | 0.706 | 0.719 | 0.694 | 0.696 | 0.696 | 0.697 |
| Positive Predictive Value (PPV) | 0.152 | 0.118 | 0.135 | 0.165 | 0.186 | 0.214 |
| Negative Predictive Value (NPV) | 0.945 | 0.967 | 0.946 | 0.921 | 0.900 | 0.869 |
| Accuracy | 0.694 | 0.712 | 0.682 | 0.675 | 0.668 | 0.656 |
| Youden's Index | 0.267 | 0.321 | 0.240 | 0.198 | 0.168 | 0.137 |
| Area Under Curve (AUC) | 0.677 | 0.709 | 0.659 | 0.632 | 0.612 | 0.591 |
3.7 Primary & Secondary Outcomes: Receiver Operator Curves
3.8 Subgroup Analysis
3.8.1 Intubated & Non-Intubated Patients: Discrimination Statistics
| Discriminator Characteristics for PaO2:FiO2 Ratio | ||||||
| In Patients Receiving IPPV | ||||||
| Criteria | Hospital Mortality | ICU Mortality | 28-Day Mortality | 90-Day Mortality | 180-Day Mortality | 1-Year Mortality |
|---|---|---|---|---|---|---|
| Optimal Cutpoint | 173.333 | 173.913 | 180.000 | 179.348 | 187.778 | 175.000 |
| Sensitivity (Sn) | 0.431 | 0.463 | 0.424 | 0.408 | 0.420 | 0.367 |
| Specificity (Sp) | 0.767 | 0.764 | 0.745 | 0.746 | 0.722 | 0.759 |
| Positive Predictive Value (PPV) | 0.221 | 0.189 | 0.183 | 0.207 | 0.215 | 0.242 |
| Negative Predictive Value (NPV) | 0.897 | 0.923 | 0.906 | 0.886 | 0.872 | 0.852 |
| Accuracy | 0.722 | 0.732 | 0.707 | 0.699 | 0.675 | 0.692 |
| Youden's Index | 0.197 | 0.227 | 0.169 | 0.154 | 0.141 | 0.127 |
| Area Under Curve (AUC) | 0.627 | 0.645 | 0.610 | 0.601 | 0.592 | 0.581 |
| Discriminator Characteristics for PaO2:FiO2 Ratio | ||||||
| In Patients Not Receiving IPPV | ||||||
| Criteria | Hospital Mortality | ICU Mortality | 28-Day Mortality | 90-Day Mortality | 180-Day Mortality | 1-Year Mortality |
|---|---|---|---|---|---|---|
| Optimal Cutpoint | 253.333 | 234.694 | 252.381 | 261.905 | 264.000 | 262.162 |
| Sensitivity (Sn) | 0.589 | 0.653 | 0.558 | 0.519 | 0.488 | 0.451 |
| Specificity (Sp) | 0.712 | 0.755 | 0.714 | 0.691 | 0.686 | 0.694 |
| Positive Predictive Value (PPV) | 0.107 | 0.068 | 0.108 | 0.142 | 0.171 | 0.212 |
| Negative Predictive Value (NPV) | 0.967 | 0.988 | 0.963 | 0.936 | 0.910 | 0.874 |
| Accuracy | 0.705 | 0.753 | 0.705 | 0.675 | 0.663 | 0.656 |
| Youden's Index | 0.300 | 0.408 | 0.272 | 0.210 | 0.174 | 0.144 |
| Area Under Curve (AUC) | 0.698 | 0.763 | 0.680 | 0.640 | 0.616 | 0.596 |
3.8.2 Intubated and Non-Intubated (Excluding Patients with Treatment Limitations)
| Discriminator Characteristics for PaO2:FiO2 Ratio | ||||||
| In Patients Receiving IPPV with No Treatment Limitations | ||||||
| Criteria | Hospital Mortality | ICU Mortality | 28-Day Mortality | 90-Day Mortality | 180-Day Mortality | 1-Year Mortality |
|---|---|---|---|---|---|---|
| Optimal Cutpoint | 177.778 | 179.000 | 180.000 | 180.000 | 187.778 | 177.500 |
| Sensitivity (Sn) | 0.454 | 0.496 | 0.437 | 0.418 | 0.426 | 0.380 |
| Specificity (Sp) | 0.756 | 0.750 | 0.748 | 0.749 | 0.725 | 0.754 |
| Positive Predictive Value (PPV) | 0.183 | 0.153 | 0.158 | 0.181 | 0.189 | 0.213 |
| Negative Predictive Value (NPV) | 0.920 | 0.942 | 0.925 | 0.906 | 0.894 | 0.874 |
| Accuracy | 0.724 | 0.729 | 0.717 | 0.710 | 0.686 | 0.698 |
| Youden's Index | 0.210 | 0.246 | 0.184 | 0.167 | 0.151 | 0.133 |
| Area Under Curve (AUC) | 0.637 | 0.659 | 0.622 | 0.611 | 0.600 | 0.587 |
| Discriminator Characteristics for PaO2:FiO2 Ratio | ||||||
| In Patients Not Receiving IPPV with No Treatment Limitations | ||||||
| Criteria | Hospital Mortality | ICU Mortality | 28-Day Mortality | 90-Day Mortality | 180-Day Mortality | 1-Year Mortality |
|---|---|---|---|---|---|---|
| Optimal Cutpoint | 260.714 | 231.034 | 266.667 | 260.000 | 260.000 | 267.273 |
| Sensitivity (Sn) | 0.557 | 0.615 | 0.550 | 0.460 | 0.422 | 0.411 |
| Specificity (Sp) | 0.705 | 0.781 | 0.688 | 0.709 | 0.710 | 0.692 |
| Positive Predictive Value (PPV) | 0.057 | 0.033 | 0.059 | 0.090 | 0.116 | 0.150 |
| Negative Predictive Value (NPV) | 0.980 | 0.994 | 0.977 | 0.954 | 0.932 | 0.899 |
| Accuracy | 0.700 | 0.779 | 0.683 | 0.695 | 0.686 | 0.659 |
| Youden's Index | 0.262 | 0.396 | 0.238 | 0.170 | 0.132 | 0.103 |
| Area Under Curve (AUC) | 0.673 | 0.757 | 0.658 | 0.612 | 0.588 | 0.569 |
3.8.3 A Priori Subgroups
| Comparison of AUCs of Each Subgroup | |||
| Subgroup | Comparison | AUC 1 Vs AUC 2 | p-value |
|---|---|---|---|
| Day 1 IPPV | Yes Vs No | 0.628 Vs 0.701 | <0.001 |
| IPPV Any Time | Yes Vs No | 0.627 Vs 0.698 | <0.001 |
| NIV Any Time | Yes Vs No | 0.622 Vs 0.668 | <0.001 |
| ECMO Any Time | Yes Vs No | 0.516 Vs 0.675 | <0.001 |
| Admission Diagnosis | Cardiac Vs NeuroSurgery | 0.62 Vs 0.641 | 0.008 |
| Cardiac Vs Post-Operative | 0.62 Vs 0.647 | <0.001 | |
| Cardiac Vs Medical | 0.62 Vs 0.644 | <0.001 | |
| Cardiac Vs Sepsis | 0.62 Vs 0.661 | <0.001 | |
| Neurosurgery Vs Post-Operative | 0.641 Vs 0.647 | 0.326 | |
| Neurosurgery Vs Medical | 0.641 Vs 0.644 | 0.587 | |
| Neurosurgery Vs Sepsis | 0.641 Vs 0.661 | 0.001 | |
| Post-Operative Vs Medical | 0.647 Vs 0.644 | 0.422 | |
| Post-Operative Vs Sepsis | 0.647 Vs 0.661 | 0.006 | |
| Medical Vs Sepsis | 0.644 Vs 0.661 | <0.001 | |
| Age Categories | Age <44 Vs Age 45-64 | 0.704 Vs 0.675 | <0.001 |
| Age <44 Vs Age 65-84 | 0.704 Vs 0.67 | <0.001 | |
| Age <44 Vs Age >84 | 0.704 Vs 0.67 | <0.001 | |
| Age 45-64 Vs Age 65-84 | 0.675 Vs 0.67 | 0.116 | |
| Age 45-64 Vs Age >84 | 0.675 Vs 0.67 | 0.309 | |
| Age 65-84 Vs Age >84 | 0.67 Vs 0.67 | 0.96 | |
| Sex | Male Vs Female | 0.671 Vs 0.684 | <0.001 |
| Frailty | Fit/Well Vs Mild Frailty | 0.687 Vs 0.667 | <0.001 |
| Fit/Well Vs Moderate/Severe Frailty | 0.687 Vs 0.638 | <0.001 | |
| Mild Frailty Vs Moderate/Severe Frailty | 0.667 Vs 0.638 | <0.001 | |
| Treatment Limitations | Yes Vs No | 0.624 Vs 0.68 | <0.001 |